@@ -171,12 +171,10 @@ def calculate_oversampled_kernel_indices(subpixel_coord, oversampling):
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dtype: float, shape: `(n_vis, 2)`.
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oversampling (int): How many oversampled pixels to one regular pixel.
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Returns:
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- oversampled_kernel_idx (numpy.ndarray): Corresponding oversampled pixel
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- indexes. These are in oversampled pixel widths from the kernel
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- centre pixel, to a maximum of half a regular pixel, so they have
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- integer values ranging from
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- ``-oversampling/2`` to ``oversampling/2``.
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- dtype: int, shape: `(n_vis, 2)`.
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+ numpy.ndarray: Corresponding oversampled pixel indexes. These are in oversampled pixel
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+ widths from the kernel centre pixel, to a maximum of half a regular
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+ pixel, so they have integer values ranging from ``-oversampling/2`` to
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+ ``oversampling/2``. [Dtype: ``int``, shape: ``(n_vis, 2)``].
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"""
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subpixel_coord = np .atleast_1d (subpixel_coord )
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assert (- 0.5 <= subpixel_coord ).all ()
@@ -207,8 +205,7 @@ def populate_kernel_cache(kernel_func, support, oversampling):
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cache_size = ((oversampling // 2 * 2) + 1)**2
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Returns:
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- cache (dict): Dictionary mapping oversampling-pixel offsets to
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- normalised kernels.
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+ dict: Dictionary mapping oversampling-pixel offsets to normalised kernels.
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"""
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# We use floordiv and multiply to give sensible results for both odd / even
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# oversampling values:
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